A T2-based water suppressed diffusion MRI (T2wsup-dMRI) was proposed to solve the CSF partial volume effects (CSF-PVE) in quantifying several parameters in tissue. There a simple closed form (CF) algorithm was used but errors were increased when tissue T2, T2t is long (> 100ms). In this study, to reduce those errors, several algorithms using least-squares (LSQ) fitting method were assessed by simulation and in vivo data. Through this study, the combined algorithm of single and bi-exponential LSQ applied in 2D (TE, b) space is the best in keeping those accuracies especially when applied in random data pattern.
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